Statistical analysis of TEC perturbations over a low latitude region during 2009–2013 ascending solar activity phase

Andima, Geoffrey; Jurua, Edward; Amabayo, Emirant B.; Habarulema, John Bosco

doi:10.1016/j.asr.2015.09.021

Cited by 3 publications

(4 citation statements)

References 27 publications

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“…Ionospheric variability over the low latitude region of Africa, based on TEC analysis, has been reported before (e.g Adewale et al 2011;Olwendo et al 2012;Habarulema et al 2013;Andima et al 2015). From these studies, the diurnal, seasonal, disturbed and quiet time TEC characteristics over the region have been revealed.…”

Section: Introductionmentioning

confidence: 54%

“…Diurnal variation of root mean square error (rmse) of IRI TEC, CODE's TEC and EOF TEC relative to GPS TEC over Malindi uncertainty in predicting the observed TEC was higher in 2013 than in 2009. This could be due to intensification of equatorial electrodynamic processes and the associated effects such as TEC perturbations during higher solar activity years(Andima et al, 2015). These secondary effects of the equatorial dynamo processes are not probably well captured by the models.…”

mentioning

confidence: 96%

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Modeling of GPS total electron content over the African low latitude region using empirical orthogonal functions

Andima¹,

Amabayo²,

Jurua³

et al. 2018

Preprint

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Abstract. In this paper, an empirical total electron content (TEC) model and trends in TEC over the African low latitude region are presented. GPS-derived TEC data from Malindi, Kenya (geographic coordinates 40.194° E, 2.996° S) and global ionospheric maps (GIMs) were used. We employed empirical orthogonal function (EOF) analysis method together with least square regression to model the TEC. The EOF-based TEC model was validated through comparisons with GIMs, GPS-derived TEC and TEC derived from the International Reference Ionosphere-2016 (IRI-2016) model for selected quiet and storm conditions. The single station EOF-based TEC model over Malindi satisfactory reproduced the known diurnal, semiannual and annual variations in the TEC. Comparison of the EOF-based TEC model results with TEC derived from IRI-2016 model showed that the EOF-based model predicted the TEC over Malindi with less errors than the IRI-2016. For the selected storms, the EOF-based TEC model simulated the storm time TEC response over Malindi better than the IRI-2016. In the case of the regional model, the EOF-based TEC model was able to reproduce the TEC characteristics in the equatorial ionization anomaly region. The EOF-based TEC model was then used as a background in estimating TEC trends. A latitudinal dependence in the trends was observed over the African low latitude region.

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Section: Introductionmentioning

confidence: 54%

mentioning

confidence: 96%

Modeling of GPS total electron content over the African low latitude region using empirical orthogonal functions

Andima¹,

Amabayo²,

Jurua³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Ionospheric variability over the low-latitude region of Africa, based on TEC analysis, has been reported before (e.g., Adewale et al, 2011;Olwendo et al, 2012;Habarulema et al, 2013;Andima et al, 2015). From these studies, the diurnal, seasonal, disturbed and quiet-time TEC characteristics over the region have been revealed.…”

Section: Introductionmentioning

confidence: 57%

“…5, the uncertainty in predicting the observed TEC was higher in 2013 than in 2009. This could be due to intensification of equatorial electrodynamic processes and the associated effects, such as TEC perturbations during higher solar activity years (Andima et al, 2015). These secondary effects of the equatorial dynamo processes are probably not well captured by the models.…”

Section: Discussionmentioning

confidence: 97%

Modeling of GPS total electron content over the African low-latitude region using empirical orthogonal functions

et al. 2019

Self Cite

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Abstract. In this paper, an empirical total electron content (TEC) model and trends in the TEC over the African low-latitude region are presented. GPS-derived TEC data from Malindi, Kenya (geographic coordinates 40.194∘ E, 2.996∘ S), and global ionospheric maps (GIMs) were used. We employed an empirical orthogonal function (EOF) analysis method together with least-squares regression to model the TEC. The EOF-based TEC model was validated through comparisons with GIMs, the GPS-derived TEC and the TEC derived from the International Reference Ionosphere 2016 (IRI-2016) model for selected quiet and storm conditions. The single-station EOF-based TEC model over Malindi satisfactorily reproduced the known diurnal, semiannual and annual variations in the TEC. Comparison of the EOF-based TEC model results with the TEC derived from the IRI-2016 model showed that the EOF-based model predicted the TEC over Malindi with fewer errors than the IRI-2016. For the selected storms, the EOF-based TEC model simulated the storm time TEC response over Malindi better than the IRI-2016. In the case of the regional model, the EOF-based TEC model was able to reproduce the TEC characteristics in the equatorial ionization anomaly region. The EOF-based TEC model was then used as a background for estimating TEC trends. A latitudinal dependence in the trends was observed over the African low-latitude region.

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Analysis of total electron content over the African low-latitude region during the maximum phase of solar cycle 24 (2012–2014)

Falayi,

Amaechi,

Oluwafemi

2024

Journal of Atmospheric and Solar-Terrestrial Physics

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Statistical analysis of TEC perturbations over a low latitude region during 2009–2013 ascending solar activity phase

Cited by 3 publications

References 27 publications

Modeling of GPS total electron content over the African low latitude region using empirical orthogonal functions

Modeling of GPS total electron content over the African low latitude region using empirical orthogonal functions

Modeling of GPS total electron content over the African low-latitude region using empirical orthogonal functions

Analysis of total electron content over the African low-latitude region during the maximum phase of solar cycle 24 (2012–2014)

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